Abstract: A controller of a data storage device includes: a host interface providing an interface to a host computer; a flash translation layer (FTL) translating a logical block address (LBA) to a physical block address (PBA) associated with an input/output (I/O) request; a flash interface providing an interface to flash media to access data stored on the flash media; and one or more deep neural network (DNN) modules for predicting an I/O access pattern of the host computer. The one or more DNN modules provide one or more prediction outputs to the FTL that are associated with one or more past I/O requests and a current I/O request received from the host computer, and the one or more prediction outputs include at least one predicted I/O request following the current I/O request. The FTL prefetches data stored in the flash media that is associated with the at least one predicted I/O request.

Abstract: A controller of a data storage device includes: a host interface providing an interface to a host computer; a flash translation layer (FTL) translating a logical block address (LBA) to a physical block address (PBA) associated with an input/output (I/O) request; a flash interface providing an interface to flash media to access data stored on the flash media; and one or more deep neural network (DNN) modules for predicting an I/O access pattern of the host computer. The one or more DNN modules provide one or more prediction outputs to the FTL that are associated with one or more past I/O requests and a current I/O request received from the host computer, and the one or more prediction outputs include at least one predicted I/O request following the current I/O request. The FTL prefetches data stored in the flash media that is associated with the at least one predicted I/O request.

Abstract: A Processing-In-Memory (PIM) model in which computations related to the POPCOUNT and logical bitwise operations are implemented within a memory module and not within a host Central Processing Unit (CPU). The in-memory executions thus eliminate the need to shift data from large bit vectors throughout the entire system. By off-loading the processing of these operations to the memory, the redundant data transfers over the memory-CPU interface are greatly reduced, thereby improving system performance and energy efficiency. A controller and a dedicated register in the logic die of the memory module operate to interface with the host and provide in-memory executions of popcounting and logical bitwise operations requested by the host. The PIM model of the present disclosure thus frees up the CPU for other tasks because many real-time analytics tasks can now be executed within a PIM-enabled memory itself. The memory module may be a Three Dimensional Stack (3DS) memory or any other semiconductor memory.

Abstract: A request management subsystem is configured to establish service classes for clients that issue requests for a shared resource on a computer system. The subsystem also is configured to determine the state of the system with respect to bandwidth, current latency, frequency and voltage levels, among other characteristics. Further, the subsystem is configured to evaluate the requirements of each client with respect to latency sensitivity and required bandwidth, among other characteristics. Finally, the subsystem is configured to schedule access to shared resources, based on the priority class of each client, the demands of the application, and the state of the system. With this approach, the subsystem may enable all clients to perform optimally or, alternatively, may cause all clients to experience an equal reduction in performance.